{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('XL_gossip_history.json', 'rb') as f:\n",
    "    gossip = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=ast.literal_eval(gossip)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loss_gossip=x['loss']\n",
    "valid_loss_gossip=x['val_loss']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[73.65263528966761,\n",
       " 42.06227253047855,\n",
       " 25.42288077751716,\n",
       " 15.96665608008782,\n",
       " 10.457916751179424,\n",
       " 7.142238098376995,\n",
       " 5.072397896483705,\n",
       " 3.751464569699633,\n",
       " 2.8367224909089783,\n",
       " 2.1993272593209556]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_loss_gossip[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[54.02071739439408,\n",
       " 32.12491841265675,\n",
       " 19.83803161243668,\n",
       " 12.747793170672844,\n",
       " 8.580143243769454,\n",
       " 5.988362028236524,\n",
       " 4.351829749872322,\n",
       " 3.3314216035836157,\n",
       " 3.4741105827762886,\n",
       " 2.072569985777245]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid_loss_gossip[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('XL_poli_history.json', 'rb') as f:\n",
    "    pol = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "y=ast.literal_eval(pol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loss_poli=y['loss']\n",
    "valid_loss_poli=y['val_loss']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[101.86458267251963,\n",
       " 98.43417989175151,\n",
       " 95.83458715724194,\n",
       " 93.3286547122665,\n",
       " 90.95214835740137,\n",
       " 88.70452059848415,\n",
       " 86.52742543057819,\n",
       " 84.41275018406665,\n",
       " 82.37008394656844,\n",
       " 80.3458257159536]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_loss_poli[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[102.10047677847055,\n",
       " 98.30010458139273,\n",
       " 95.2431887113131,\n",
       " 92.60741894061749,\n",
       " 90.20074991079477,\n",
       " 87.94391808143028,\n",
       " 85.75263038048378,\n",
       " 83.6416238638071,\n",
       " 81.56866689828726,\n",
       " 79.60847825270433]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid_loss_poli[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot(train_loss_gossip)\n",
    "plt.plot(valid_loss_gossip)\n",
    "plt.plot(train_loss_poli)\n",
    "plt.plot(valid_loss_poli)\n",
    "plt.ylim(0,100)\n",
    "plt.xlim(0,80)\n",
    "plt.title('Model loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train_Loss_Gossip', 'Test_Loss_Gossip','Train_Loss_Politifact','Test_Loss_Politifact'], loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[77.97401827832202,\n",
       " 47.87124101865542,\n",
       " 30.739250873256992,\n",
       " 20.26285545356743,\n",
       " 13.77697965848696,\n",
       " 9.57223897718645,\n",
       " 6.8209688895470375,\n",
       " 4.993705043354472,\n",
       " 3.744918523134885,\n",
       " 2.870271435460368]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_loss_poli[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# plt.plot(train_loss_gossip)\n",
    "# plt.plot(valid_loss_gossip)\n",
    "plt.plot(train_loss_poli)\n",
    "plt.plot(valid_loss_poli)\n",
    "# plt.ylim(-2, 2)\n",
    "plt.xlim(0,20)\n",
    "plt.title('Model loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train_Loss_Politifact','Test_Loss_Politifact'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot(train_loss_gossip)\n",
    "plt.plot(valid_loss_gossip)\n",
    "# plt.plot(train_loss_poli)\n",
    "# plt.plot(valid_loss_poli)\n",
    "# plt.ylim(-2, 2)\n",
    "plt.xlim(0,20)\n",
    "plt.title('Model loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train_Loss_Gossip', 'Test_Loss_Gossip'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (BERT)",
   "language": "python",
   "name": "bert"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
